=== Installation for Linux ===

The scripts linked below have been tested under Ubuntu 20.4 LTS and 20.10, and Debian 10 (Buster) and will work fine for both desktop and server variants and likely other Debian based distros like Mint.

Because of package name differences and in Buster the broken state of the xcb-utils package the installer is hard-coded to detect either of these distro variants and install the correct packages, so if you want to install to some other flavour then you'll likely need to roll-your-own, albeit the install script will give you a good starting point.

To start, download both of the following to your home directory (~/)

'''wget https://gist.githubusercontent.com/edharman/dc8dc37d5f9216c97c345c6b0abab251/raw/4a11cfbc508eed48ce6143e2b4c50850d393bd7f/install.sh'''

'''wget https://gist.githubusercontent.com/edharman/dc8dc37d5f9216c97c345c6b0abab251/raw/4a11cfbc508eed48ce6143e2b4c50850d393bd7f/opencv4_install.sh'''

You should have 2 new files in your directory-

install.sh

opencv4_install.sh

Next -

'''chmod +x *.sh'''

You may want to edit the opencv4_install.sh to both reflect the GPU you may be using and optimise the compile time by adjusting the number of threads to use whilst compiling - this is controlled by the line

make -j4 -- 4 being the No. of threads to use

If using an NVIDIA GPU you'll need to google for the device specific instructions and compile flags..

By default VAAPI support is assumed and both gstreamer and ffmpeg capture enabled, so if you are using Intel chipsets with Iris integrated GPU's you are good to go, albeit you will need to install the Intel drivers and VAAPI support Ubuntu instructions [http://lifestyletransfer.com/how-to-install-gstreamer-vaapi-plugins-on-ubuntu/]

The install procedure at some point clones the opencv repository which itself contains an opencv4_intall.sh which is not optimised for Intel chipsets, however this install script will copy the one from your home directory and execute that instead.

Next execute the install script -

'''./install.sh'''

You will immediately be prompted to enter your sudo password before the procedure continues....

If you are installing on a Debian distro the script will then run without intervention to completion, if using a Ubuntu distro you will at some point be prompted to accept an EULA licence for the TrueType fonts install.

Since you likely have not got mouse support in a terminal window to navigate the EULA screens -

At the first screen, hit the tab button and the <OK> box should be highlighted red, then hit return.

At the second screen hit the tab once and the <Yes> option should be highlighted in red, then press return - the install process will then continue to completion.

The install script may take some time dependant on the hardware you have, I have tested this on an Intel i3 physical server and on an i6 running VM's under Hyper-V and on the latter with 10 threads enabled the install time is under 30 minutes, YMMV..

Upon completion (and I am assuming a headless 'server' distro install) in the shell window -

'''source vRMS/bin/activate''' # to enter the vRMS env

'''cd source/RMS''' # to enter the default working directory

Next steps are to edit and customise your .config file to reflect your station location, camera config and storage directory and any other site specific details -

'''nano ./config'''

Assuming you are using an IP camera the capture device string will be something like -

1. using gstreamer with VAAPI acceleration -

'''device: rtspsrc location=rtsp://<camera-ip>:554/user=admin&password=&channel=1&stream=0.sdp ! rtpjitterbuffer ! rtph264depay ! h264parse ! vaapidecodebin ! videoconvert ! appsink'''

2. Alternatively using FFMPEG with no hardware acceleration -

'''device: rtsp://<camera-ip>:554/user=admin&password=&channel=1&stream=0.sdp'''

Save the .config and test that you can see the camera stream -

On a desktop run the ShowLiveStream script by clicking on the icon

On a headless machine (and assuming you have X-11 forwarding support '''and''' a remote X-11-Server on your desktop , more on that in another post [https://gist.github.com/edharman/2ab7976a71c413e9617add12dc94b278 here]...

In the shell terminal -

'''python -m Utils.ShowLiveStream'''

...after a few seconds whilst cython will check it is up to date you should see a new window open showing the live stream..

Hitting CTRL-C in the launch window will kill it...

To start a capture -
On a desktop install click the RMS_StartCapture link on the desktop.

On a headless system I use -

'''nohup ./Scripts/RMS_StartCapture.sh &> /dev/null &'''

This redirects stderr & stdout to /dev/null (i.e. throws it away) and the final & backgrounds the process so the you can disconnect the terminal session and leave the process running.

To run SkyFit2 -

'''python -m Utils.SkyFit2 <path to .fits capture directory>'''

I find this is pretty quick and responsive even on a lowly i3 processor and running headless.

2021-06-27T15:28:29Z

Stargazer: /* RMS Software Installation */

Welcome to the Global Meteor Network's wiki page!

The Global Meteor Network (GMN) is a world wide organization of amateur and professional astronomers alike, whose goal is to observe the night sky using low-light video cameras and produce meteor trajectories in a coordinated manner. Here you will find information on the purpose and structure of the GMN, assembling and operating your own meteor camera, contributing to the development of RMS the GMN software, as well as information on how your observations as a citizen scientist can contribute to the further understanding of our solar system's formation and evolution.

'''If you have come here to find out how to build and setup a camera from scratch, jump ahead to [https://globalmeteornetwork.org/wiki/index.php?title=Main_Page#How_do_I_obtain_a_camera.3F this] section !'''

== Global Meteor Network Overview ==

=== [https://globalmeteornetwork.org/?page_id=141 Our mission] ===

=== [https://globalmeteornetwork.org/?p=363 A brief history of the Global Meteor Network] ===

=== [https://youtu.be/oM7lfQ4nmyw Video overview - Meteor tracking and the GMN from Astro Imaging Channel presentation] ===

=== [https://globalmeteornetwork.org/data/ Some 'live' GMN data products] ===

== Meteor Detection Station ==

=== What is an RMS GMN station? ===
: A RMS-based GMN station that is the subject of this Wiki consists of a Raspberry Pi (RPi) single board computer, a low light level security video camera, and the RMS software package. The camera is securely mounted in a weatherproof housing, pointed at the sky, and connected to the RPi with a POE (Power Over Ethernet) cable. The RPi is connected to the Internet via WiFi, and to be a part of GMN network, you’ll need a fairly powerful Raspberry Pi (RPi 3B+, RPi 4 or better) and a reasonably fast Internet connection. The internet connection is primarily required to enable data upload to a central server each morning as well as provide automatic updates for the RMS software.

: Nightly, the RPi starts recording video from the camera shortly after local sunset continuously compressing and storing the video data locally. Each morning before sunrise, after capture is complete, the RPi analyzes the video and extracts your nightly station’s meteor observations. These extracted video “clips” of detected meteors are then archived and uploaded to a server. The clips can total hundreds of megabytes on a “busy” night (e.g., in a heavy meteor shower, or a night with a lot of false detections--progress is being made on the detection software). The server finds meteors which were observed with more than one station and this enables the server to triangulate the meteor trails in 3D and calculate the orbits of the meteors.

===[https://github.com/CroatianMeteorNetwork/RMS/blob/master/README.md What do I need?] ===

You'll need a Raspberry Pi with the software on, and a camera kit. We strongly recommend the Pi4 model. The software will run on a Pi3 but it is much slower.

=== How do I obtain a camera? ===
There are two options:

==== Buy a Camera ====
You can buy a camera and Pi prebuilt and ready to install. These are available from a couple of suppliers. The Croatian Meteor Network sell prebuilt cameras as explained on [https://globalmeteornetwork.org/?page_id=136 this page]. Alternatively, if you're in the UK, you can obtain cameras from the [https://ukmeteornetwork.co.uk/ UK Meteor Network]

==== Build your own from scratch ====
This requires some basic DIY skills and some familiarity with the Raspberry PI, but don't be put off. The instructions are comprehensive and if you get stuck, you can ask for advice in the [https://groups.io/g/globalmeteornetwork groups.io] forum.

Click on this link if you want to '''[[Build_A_Camera|build a camera from scratch]]'''.

Once you've built the camera, You can '''[https://globalmeteornetwork.org/wiki/index.php?title=Main_Page#Flash_a_pre-built_image flash a Prebuilt image]''' onto an SD card to set up the Pi with the software required to capture meteors and upload data to the network.

=== Can I use a commercial all-sky camera? ===

: Generally no due to the lack of sensitivity. [https://globalmeteornetwork.org/?p=163 But see this recent experiment]

== Operating and maintaining your GMN station ==

=== Overview ===

: Please note that GMS is a nascent operation and you may share some growing pains if you choose to be involved -- we're still working out some bugs and making improvements here, which may be an opportunity to help if you have programming skills! ;-) So note that the workload of day-to-day operation can be non-zero, and might take a little bit of your time.

: Ideally, you'll want to monitor your RMS RPi system(s) daily to look for freezes or glitches or other problems... like birds nesting or soiling the camera window, people accidentally unplugging the power cord, mice (or cats or dogs!) chewing on the camera Ethernet cable, etc.

: Although we are getting close, this is not a "power up and forget about it" system yet.
: However, by its very nature, the GMS network is inhabited by a lot of people who are willing to help newcomers getting started. So, here are some clues for daily operation of your RMS camera.

=== So what does the meteor camera do over the course of 24 hours? ===

: The RMS Python based system calculates the sundown to sunrise interval and schedules video camera capture all night long. Depending on the video camera and capabilities of the RPi, the camera captures 25 or more frames per second between evening and morning twilight. During the continuous image capture, the station begins processing captured image data, doing a pre-screening to target frames with a suitable number of stars (usually around 20) that makes it worth looking for meteor detections. Once data capture has finished, the station switches into processing all the promising frames for detections, then refining the astrometric accuracy of every positive detection. Using the station platepar (plate parameters) calibration file, processing iterates to find the best astrometry and photometry solution for each detected meteor. Once this process has analyzed each detection, summary files are created.
: These summary files include text file data presentation in several widely accepted formats (CAMS and UFOorbit), as well as graphic plots of detection frequencies throughout the night, a set of thumbnail images of detections, a set of thumbnail images of data captured throughout the night, a single image with all detections stacked together, plots of photometry, astrometry, and camera pointing drift in arc minutes throughout the course of the night as the mount or building flexes, a flat file for correcting images, and a plot of all detections showing any identified radiants. Finally all results are combined into a single compressed archive, which is automatically uploaded each morning to the central server. Optionally, you can create a mp4 movie showing a time lapse of the night’s captured images.
: Each morning you can review the result files on the RPi, and copy anything you want to your computer or tablet.

===Archiving data and backing up configuration ===

: Data backup is as much or as little as you like. Your primary data is automatically uploaded to the central server every morning when data processing is done. We've built some automated tools that can help to back up any additional data to a thumb drive inserted into the RPi.

=== Viewing the data ===

: To view the data, you can use CMN_binViewer software[https://github.com/CroatianMeteorNetwork/cmn_binviewer] which is already installed in the RMS SD image.
: There is also a Windows version[https://www.dropbox.com/s/44u5r9nso81wa56/CMN_binViewer_setup_x64.exe?dl=1] you can install.

=== Tools and Utilities ===

* [https://www.realvnc.com/en/connect/download/viewer/ RealVNC] or [https://anydesk.com/en AnyDesk] remote connect tool allows station access from anywhere. Access from outside your network is enabled by use of an OpenVPN connection address available to meteor stations. Alternatively, with VNC and Teamviewer, you can create an account and team on their websites, and then remotely access your station.
* Samba data directory access, allows you to copy data results directly from your RPi to your computer or tablet.
* [https://github.com/CroatianMeteorNetwork/cmn_binviewer CMN_binViewer] can be used to view standard fits image files containing meteor detections. It runs on the RPi, and is also available under Windows.
* [https://sonotaco.com/soft/e_index.html UFO Orbit] allows you to process data from multiple stations and generate unified radiants of two or more stations seeing the same meteor. It can plot the shared object ground path, orbital characteristics, and can output a summary file of all objects seen by more than one station, which can be used for further analysis.
* RMS software can be installed under Windows to allow much of the RMS python-based code to be executed on your computer, so it can be run against meteor station data you have transferred to your computer from the RPi.
* You can run RMS Python jobs on the RPi to sample the image files captured all night long and condense them into a mp4 movie. This creates a sometimes mesmerizing summary that can run for over 2 minutes in length for winter time data.

== Configuring and installing your camera ==

=== [https://docs.google.com/document/u/1/d/1MTL85YMYH33u8OZ9Tl0JjSZXcLn8mOmNrCOC0I28Drw/edit Quick start guide] ===

=== [[Focusing_your_camera | Focusing your IP camera]] ===

=== [https://www.youtube.com/watch?v=N2sq1hBwcAA Video tutorial - Configuring your IMX291 IP camera] ===

=== [https://docs.google.com/document/d/1TPotXcRstHz-XWIQYIW71xkRYy7Ca1UCoEiZsqdk9zw/edit?usp=sharing Different ways of connecting the camera] ===

== What can I do with my GMN station? ==

=== [https://www.youtube.com/watch?v=MOjb3qxDlX4 Video Tutorial - Using SkyFit2 to perform astrometric and photometric calibration + Manually reducing observations of fireballs and computing their trajectories] ===

=== [https://globalmeteornetwork.org/?p=310 Generating a Google Earth KML file to show your station's field of view] ===

=== [https://globalmeteornetwork.org/?p=253 Using UFO Orbit program to estimate meteor trajectories] ===

=== [https://globalmeteornetwork.org/?p=221 Urban meteor observing] ===

== RMS Software Installation ==

=== Flash a pre-built image ===

Pre-built Images are available with the RMS software pre-installed on Raspbian. Raspbian is the operating system typically used on the Raspberry Pi.

A 128 GB microSD card is preferred, although smaller 64 GB cards will also work. The image is flashed to the microSD card using the Etcher utility for Windows (32 or 64-bit), MacOS or Linux (64-bit), which can be found [https://www.balena.io/etcher/ here]

When you first boot up the Pi make sure you have a keyboard, monitor and mouse attached as you will be taken through a setup process by the RMS software.

The current publicly released images of RMS are:
[https://www.dropbox.com/s/sa9csd4m3jr1vqo/RMS_image_20191203.zip?dl=1 RPi3B+ ]
and
[https://www.dropbox.com/s/a6ix7nz9f27h03d/RMS_RPi4_image_20200604.zip?dl=1 RPi4 ].

Please see the [https://docs.google.com/document/u/1/d/1MTL85YMYH33u8OZ9Tl0JjSZXcLn8mOmNrCOC0I28Drw/edit Quick Start Guide] about how to flash them to an SD card.

Notes:
* The earlier versions of the Raspberry Pi, the 1 and 2, are not powerful enough to run RMS software.

* the pre-installed RMS software images incorporate an auto-updating feature, so that the RMS software is updated to the current release whenever your Raspberry Pi RMS is booted. This way, your station is always running the most recent set of updates.

* For installations into other Linux or windows environments, executing the command ''git pull'' will update to the most recent RMS release.

* The code was designed to run on a RPi, but it will also run an some Linux distributions. We have tested it on Linux Mint 18 and Ubuntu 16. For information on installing into other Linux releases, check portions of the section listed below for installing on RPi, and also check installation instructions found on [https://github.com/CroatianMeteorNetwork/RMS GitHub]

=== Build the software from scratch (not for the faint-hearted) ===

If you'd like to install RMS on the RPi from scratch (not recommended), you can follow these installation instructions:

=== [https://docs.google.com/document/d/1ChaXx6WkuGfcQ_f5yRbwUOOMxEgIJrjq932UZE6cRjE/edit Install for Raspberry Pi 3] ===
=== [https://docs.google.com/document/d/19ImeNqBTD1ml2iisp5y7CjDrRV33wBeF9rtx3mIVjh4/edit?usp=sharing Install for Raspberry Pi 4] ===

=== Installation for Windows ===
Note that installation for Windows is optional. However, if you want to run RMS tools on your PC, where its much quicker to run SkyFit2 to calibrate your camera to the sky, or you want to use BatchFFToImage to convert data to jpeg format to share on Social Media, Click '''[[Windows_Installation|here]]''' for instructions.

Note that data capture and meteor detection does not work under windows! If you are a Windows whizz, please feel free to investigate why this doesn't work.

Finally: these instructions have been tested on Windows 10 64-bit but should work for any version of Windows that Anaconda and Git are available for.

=== Installation for MacOS ===
Installation for MacOS is optional as it is for Windows. If you do want to install it, please follow the instructions '''[[MacOS_Install | here]]'''.

=== Installation for Linux ===

The scripts linked below have been tested under Ubuntu 20.4 LTS and 20.10, and Debian 10 (Buster) and will work fine for both desktop and server variants and likely other Debian based distros like Mint.

Because of package name differences and in Buster the broken state of the xcb-utils package the installer is hard-coded to detect either of these distro variants and install the correct packages, so if you want to install to some other flavour then you'll likely need to roll-your-own, albeit the install script will give you a good starting point.

To start, download both of the following to your home directory (~/)

'''wget https://gist.githubusercontent.com/edharman/dc8dc37d5f9216c97c345c6b0abab251/raw/4a11cfbc508eed48ce6143e2b4c50850d393bd7f/install.sh'''

'''wget https://gist.githubusercontent.com/edharman/dc8dc37d5f9216c97c345c6b0abab251/raw/4a11cfbc508eed48ce6143e2b4c50850d393bd7f/opencv4_install.sh'''

You should have 2 new files in your directory-

install.sh

opencv4_install.sh

Next -

'''chmod +x *.sh'''

You may want to edit the opencv_install.sh to both reflect the GPU you may be using and optimise the compile time by adjusting the number of threads to use whilst compiling - this is controlled by the line make -j4 <-4 being the No. of threads

By default VAAPI support is assumed and both gstreamer and ffmpeg capture enabled, so if you are using Intel chipsets with Iris integrated GPU's you are good to go, albeit you will need to install the Intel drivers and VAAPI support Ubuntu instructions [http://lifestyletransfer.com/how-to-install-gstreamer-vaapi-plugins-on-ubuntu/]

The install procedure at some point clones the opencv repository which itself contains an opencv4_intall.sh which is not optimised for Intel chipsets, however this install script will copy the one from your home directory and execute that instead.

Next execute the install script -

'''./install.sh'''

You will immediately be prompted to enter your sudo password before the procedure continues....

If you are installing on a Debian distro the script will then run without intervention to completion, if using a Ubuntu distro you will at some point be prompted to accept an EULA licence for the TrueType fonts install.

The install script may take some time dependant on the hardware you have, I have tested this on an Intel i3 physical server and on an i6 running VM's under Hyper-V and on the latter with 10 threads enabled the install time is under 30 minutes, YMMV..

Upon completion (and I am assuming a headless 'server' distro install) in the shell window -

'''source vRMS/bin/activate''' # to enter the vRMS env

'''cd source/RMS''' # to enter the default working directory

Next steps are to edit and customise your .config file to reflect your station location, camera config and storage directory and any other site specific details -

'''nano ./config'''

Assuming you are using an IP camera the capture device string will be something like -

1. using gstreamer with VAAPI acceleration -

'''device: rtspsrc location=rtsp://192.168.0.150:554/user=admin&password=&channel=1&stream=0.sdp ! rtpjitterbuffer ! rtph264depay ! h264parse ! vaapidecodebin ! videoconvert ! appsink'''

2. Alternatively using FFMPEG with no hardware acceleration -

'''device: rtsp://<camera-ip>:554/user=admin&password=&channel=1&stream=0.sdp'''

Save the .config and test that you can see the camera stream -

On a desktop run the ShowLiveStream script by clicking on the icon

On a headless machine (and assuming you have X-11 forwarding support '''and a remote X-11-Server on your desktop''', more on that in another post [https://gist.github.com/edharman/2ab7976a71c413e9617add12dc94b278 here]...

In the shell terminal -

'''python -m Utils.ShowLiveStream'''

...after a few seconds whilst cpython will check it is up to date you should see a new window open showing the live stream..

Hitting CTRL-C in the launch window will kill it...

To start a capture -
On a desktop install click the RMS_StartCapture link on the desktop.

On a headless system I use -

'''nohup ./Scripts/RMS_StartCapture.sh &> /dev/null &'''

This redirects stderr & stdout to /dev/null (i.e. throws it away) and the & backgrounds the process so the you can disconnect the terminal session and leave the process running.

To run SkyFit2 -

'''python -m Utils.SkyFit2 <path to .fits capture directory>'''

I find this is pretty quick and responsive even on a lowly i3 processor and running headless.

== FAQ ==

=== What should I back up when re-flashing an SD card? ===

: The .config, platepar and mask files that are in the RMS source directory, plus the whole contents of the hidden directory /home/pi/.ssh.

If your SD card fails or becomes corrupted, the config files can be fetched from the server as they are uploaded every day together with the data. However the contents of .ssh are essential for connection to the server, so you must also save these

=== What are the values in FTPdetectinfo_* file designated as hnr mle bin Pix/fm Rho Phi? ===

: Some of these values are not used in RMS (hnr mle bin), but they are in CAMS, so they are here to conform to the standard. Thus they are all zeros. The others are:

: - Pix/fm - Average angular speed of the meteor in pixels per frame.

: - Rho, Phi - Parameters that define the line of the meteor in polar coordinates, see [https://en.wikipedia.org/wiki/Hough_transform#Theory here] for more details. Rho is the distance of the line from the centre of the image, and phi is the angle of the line as measured from the positive direction of the Y axis (basically a line going from the center of the image to the top of the image), the positive angles are measured clockwise (I think, the CAMS standard might define these parameters a bit differently, the Y axis is flipped).

: The intensity is the sum of all pixel intensities of the meteor on a given frame. Let's say I represent an area around the meteor on a given frame like this, where the numbers are pixel intensities on an 8-bit image (so they can range from 0 to 255):

: [[File:Intensity_sum.png |Intensity_sum.png ]]

: and the pixels values inside the red boundary represent the meteor blob on the frame, the intensity would be the sum of all numbers inside the red boundary.
: This value is later used to compute the magnitude. The magnitude is computed as: mag = -2.5*log10(intensity sum) + photometric_offset. The photometric offset is estimated in SkyFit by fitting the line with slope -2.5 through pairs of known magnitudes of stars and logartihms of their pixel intensity sum. The photometric offset is basically the intercept of that line. The constant slope of -2.5 comes from the [https://en.wikipedia.org/wiki/Apparent_magnitude#Calculations definition of stellar magnitudes.]

== IstraStream ==

=== [http://istrastream.com/rms-gmn/ IstraStream GMN status website] ===

: The IstraStream.com is an independent hosting site which is part of our world wide GMN. It is primarily a host for data from cameras sold by IstraStream, but other station operators can request that their data be included.
To enable the IstraStream upload, simply change the config file as follows:

<pre>
; External script
; An external script will be run after RMS finishes the processing for the night, it will be passed three arguments:
; captured_night_dir, archived_night_dir, config - captured_night dir is the full path to the captured folder of the night
; the second one is the archived, and config is an object holding the values in this config file.
; ---------------
; Enable running an external script at the end of every night of processing
external_script_run: true
; Run the external script after auto reprocess. "auto_reprocess" needs to be turned on for this to work.
auto_reprocess_external_script_run: false
; Full path to the external script
external_script_path: /home/pi/source/RMS/iStream/iStream.py ; <--- CHANGE
; Name of the function in the external script which will be called
external_function_name: rmsExternal

; Daily reboot
; ---------------
; Reboot the computer daily after the processing and upload is done
reboot_after_processing: false ; <--- CHANGE
</pre>

Then, send an e-mail to [mailto:info@istrastream.com info@istrastream.com] with your:
* Station_ID
* Location or Name (if not secret)
* Lens type/size

For example, "CA0001; Elginfield Observatory, Ontario, Canada; 4mm". The IstraStream crew will enable the weblog page within a few days.

Finally, this document explains what every plot on the IstraStream weblog means:
=== [https://docs.google.com/document/d/132aHGn0QPzhpVN2s2n6FT6rJn39LAsPkchWJqXQb8Qk/edit?usp=sharing IstraStream Plots Explanation] ===

== For More Information ==

=== [https://globalmeteornetwork.org/?page_id=43 Contact the Global Meteor Network] ===

=== [https://groups.io/g/globalmeteornetwork Join the Global Meteor Network Forum] ===

=== GMN related publications ===

: [https://arxiv.org/abs/2003.05458/ Moorhead, A. V., Clements, T. D., & Vida, D. (2020). Realistic gravitational focusing of meteoroid streams. Monthly Notices of the Royal Astronomical Society, 494(2), 2982-2994.]

: [https://globalmeteornetwork.org/wordpress/wp-content/uploads/2018/11/Kukic-et-al-2018-Rolling-shutter.pdf Kukić, P., Gural, P., Vida, D., Šegon, D. & Merlak, A. (2018) Correction for meteor centroids observed using rolling shutter cameras. WGN, Journal of the International Meteor Organization, 46:5, 154-118.]

: [https://gmn.duckdns.org/wordpress/wp-content/uploads/2018/11/2018_WGN___RMS_sun_skirter_final.pdf Vida, D., Mazur, M. J., Šegon, D., Kukić, P., & Merlak, A. (2018). Compressive strength of a skirting Daytime Arietid-first science results from low-cost Raspberry Pi-based meteor stations. WGN, Journal of the International Meteor Organization, 46, 113-118.]

: [https://arxiv.org/pdf/1911.02979.pdf Vida, D., Gural, P., Brown, P., Campbell-Brown, M., Wiegert, P. (2019) Estimating trajectories of meteors: an observational Monte Carlo approach - I. Theory. arXiv:1911.02979v4 [astro-ph.EP] 21 Apr 2020]

: [https://arxiv.org/pdf/1911.11734.pdf Vida, D., Gural, P., Brown, P., Campbell-Brown, M., Wiegert, P. (2019) Estimating trajectories of meteors: an observational Monte Carlo approach - II. Results. arXiv:1911.11734v1 [astro-ph.EP] 26 Novr 2019]

: [https://gmn.duckdns.org/wordpress/wp-content/uploads/2018/11/2018_WGN___RMS_first_results-final.pdf Vida, D., Mazur, M. J., Šegon, D., Zubović, D., Kukić, P., Parag, F., & Macan, A. (2018). First results of a Raspberry Pi based meteor camera system. WGN, Journal of the International Meteor Organization, 46, 71-78.]

: [https://gmn.duckdns.org/wordpress/wp-content/uploads/2018/11/Vida_IMC2016_proceedings_final.pdf Vida, D., Zubović, D., Šegon, D., Gural, P., & Cupec, R. (2016). Open-source meteor detection software for low-cost single-board computers. In Proceedings of the International Meteor Conference (IMC2016), Egmond, The Netherlands (pp. 2-5).]

: [https://gmn.duckdns.org/wordpress/wp-content/uploads/2018/11/Zubovic_IMC2015_priceedings_final.pdf Zubović, D., Vida, D., Gural, P., & Šegon, D. (2015). Advances in the development of a low-cost video meteor station. In Proceedings of the International Meteor Conference, Mistelbach, Austria (pp. 27-30).]